First, differences in losses to follow-up and missed visits will be compared between the six comparison groups to detect any potential bias (400 IU group stratified by race: African American, Hispanic and Caucasian; 4000 IU group also stratified by race). The biggest problem with unbalanced losses will be the loss of statistical power. We will aggressively attempt to avoid any losses by monitoring adherence to visits. In the event that there are differential losses between ethnic groups or supplementation groups, we will conduct statistical tests to ascertain whether these are random or biased. Random losses will be reported but should not affect outcomes. Biased, or non-random, losses will be assessed on their potential impact on differences in outcomes. If necessary, we will conduct a propensity score analysis to control for any statistically significant differences in non-random losses. Following that, differences in compliance to supplementation will be compared as an 'intent-to-treat' design. Any significant deviation from protocol will be considered in subsequent analyses. In this section, we will report on: (1) the deviations from protocol; (2) outcomes comparisons using an efficacy design to test for true differences associated with subjects who adhered to protocol; and, (3) outcomes comparison using the intent to treat (effectiveness) design to test for actual differences that might be expected in a non-controlled intervention. This will help determine whether this type of supplementation could be expected to be effective if applied to the general population.